Abstract 3417: Effects of plasma exosome isolation methods on detectable multiomic profiles in cancer patients and healthy controls
Authors: Alex C. Soupir, Paul A. Stewart, Yury Nunez Lopez, Brandon J. Manley, Bruna Pellini, Jingsong Zhang, Qianxing Mo, Douglas C. Marchion, Min Lui, John M. Koomen, Erin M. Siegel, Liang Wang
Journal: Cancer Research (2022)

Abstract Introduction: Circulating exosomes in blood have been considered as a treasure chest for biomarker discovery in cancer. Due to their heterogeneity, different isolation methods may enrich distinct exosome cargos generating different omic profiles. In this study, we evaluated the effects of plasma exosome isolation methods on detectable multiomic profiles in cancer patients and healthy controls. Methods: Plasma exosomes were isolated from prostate cancer patients (PC; N = 11), lung cancer patients (LC; N = 13), and matched healthy controls (HC; N = 10) using three methods [SBI (size exclusion), Takara (lectin binding), and Wako (Tim4 binding)]. Mass spectrometry was performed to determine exosome lipidome and metabolome profiles. To evaluate group-specific exosome enrichment, we developed an exosome enrichment index (EEI) by summing 50 smallest p-values after log2 transformation. Higher EEI indicates prefrential capture of significant exosome cargos from patients over controls. Results: Our data showed that the SBI method generated the most identified lipids from exosome across all groups (LC = 935, PC = 939, and HC = 943), followed by Takara (245, 245 and 245) and Wako (205, 208 and 213). Compared to controls, LC patients had 31 higher and 5 lower lipid levels (FDR &amp;lt; 0.1) using the SBI and 3 higher and 1 lower level (FDR &amp;lt; 0.1) using Takara. We did not observe any differences between cancer and normal samples using Wako. The most detectable known metabolites were found in exosomes from SBI (LC = 188, PC = 191, and HC = 100), followed by Wako (LC = 107, PC = 107, and HC = 107) and Takara (LC = 99, PC = 100, and HC = 100). Of the metabolites from SBI, 5 were significantly higher (FDR&amp;lt;0.1) in PC patients than in controls. The most significant metabolite in PC was L-Cystathionine, which has been shown to be upregulated in bone-metastatic PC3 cells. Neither Takara nor Wako exosome fractions showed differently expressed metabolites between any groups. Our EEI analysis showed the highest lipid EEI from SBI in PC (474.4) and LC (906.74), while a lower lipid EEI from Takara in PC (359.9), LC (495.58), and Wako in PC (307.5) and LC (148.1). Metabolite EEI showed an EEI range from 590.3 in SBI PC to 185.6 in Takara LC. SBI, again, achieved the highest EEI for both PC and LC (357.3). Conclusion: These results support that the SBI method can capture more heterogeneous exosome populations, possibly because this size exclusion-based method does not discriminate exosomes with different protein components. In contrast, Takara and Wako methods target exosome surface proteins, enriching specific exosome subpopulations resulting in less diversity of detectable lipids and metabolites. Overall, these findings suggest that exosome isolation methods can select subpopulations and determine the exosome content, which will significantly impact exosome-based biomarker discovery. Citation Format: Alex C. Soupir, Paul A. Stewart, Yury Nunez Lopez, Brandon J. Manley, Bruna Pellini, Jingsong Zhang, Qianxing Mo, Douglas C. Marchion, Min Lui, John M. Koomen, Erin M. Siegel, Liang Wang. Effects of plasma exosome isolation methods on detectable multiomic profiles in cancer patients and healthy controls [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3417.